In this paper, we proposed a logistic regression model with lp, q regularization that could
give a group sparse solution. The model could be applied to variable-selection problems …

This article considers the problem of estimating the high-dimensional Poisson regression
model with group sparsity in the parameter vector using the weighted group Lasso method …

The optimal subsampling is an statistical methodology for generalized linear models (GLMs)
to make inference quickly about parameter estimation in massive data regression. Existing …

Recently, the high-dimensional negative binomial regression (NBR) for count data has been
widely used in many scientific fields. However, most studies assumed the dispersion …